Computer vision involves acquiring, processing, analyzing, and understanding images for use in applications. Traditionally, a processor, for example, an image sensor processor (ISP), coupled to a sensor acquires image data from the sensor and performs certain computer vision operations on the acquired image data to detect features. Programs executing on the processor may utilize the detected features in a variety of applications, such as plane detection, object classification, face detection, smile detection, and gesture detection.
Much effort has been made in recent years to enable computing devices to detect or classify features and objects in the field of view of a computing device, such as a mobile device. Capturing images in the field of view of the computing device using traditional image sensors and processing the images to extract features using conventional processors require significant processing resources, resulting in high power consumption and short battery life per charge cycle in computing devices, such as mobile devices, which are generally very sensitive to energy consumption.